Login / Signup

Clinical applicability of automated cephalometric landmark identification: Part I-Patient-related identification errors.

Chihiro TanikawaChonho LeeJaeyoen LimAyaka OkaTakashi Yamashiro
Published in: Orthodontics & craniofacial research (2021)
Artificial intelligence systems that recognize cephalometric landmarks could be applied to various patient groups. Patient-oriented errors were found in patients with cleft lip and/or palate.
Keyphrases
  • artificial intelligence
  • case report
  • machine learning
  • deep learning
  • big data
  • patient safety
  • high throughput